AI Medical Compendium Topic

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Data Mining

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Applying machine learning, text mining, and spatial analysis techniques to develop a highway-railroad grade crossing consolidation model.

Accident; analysis and prevention
The consolidation of Highway-Railroad Grade Crossing (HRGC) is one of the effective approaches to decrease the number of crashes between trains and vehicles. From 2015-2019, there were 57 HRGC crashes at crossings in East Baton Rouge Parish (EBRP), r...

A neurodynamic optimization approach to supervised feature selection via fractional programming.

Neural networks : the official journal of the International Neural Network Society
Feature selection is an important issue in machine learning and data mining. Most existing feature selection methods are greedy in nature thus are prone to sub-optimality. Though some global feature selection methods based on unsupervised redundancy ...

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.

Computational and mathematical methods in medicine
Intestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since many diagnostic measures suitable for adults are not applicable to children. The rapid development o...

A Comprehensive Survey on Graph Neural Networks.

IEEE transactions on neural networks and learning systems
Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Eu...

Data mining for pesticide decontamination using heterogeneous photocatalytic processes.

Chemosphere
Pesticides are chemical compounds used to kill pests and weeds. Due to their nature, pesticides are potentially toxic to many organisms, including humans. Among the various methods used to decontaminate pesticides from the environment, the heterogene...

Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews.

Systematic reviews
BACKGROUND: Despite existing research on text mining and machine learning for title and abstract screening, the role of machine learning within systematic literature reviews (SLRs) for health technology assessment (HTA) remains unclear given lack of ...

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome.

Nature communications
The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcrip...

How wide is the application of genetic big data in biomedicine.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As countries around the world start to build their own gene banks, scientists study the data to explore ...

LSTM-Based End-to-End Framework for Biomedical Event Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical event extraction plays an important role in the extraction of biological information from large-scale scientific publications. However, most state-of-the-art systems separate this task into several steps, which leads to cascading errors. I...

Extracting Inter-Sentence Relations for Associating Biological Context with Events in Biomedical Texts.

IEEE/ACM transactions on computational biology and bioinformatics
We present an analysis of the problem of identifying biological context and associating it with biochemical events described in biomedical texts. This constitutes a non-trivial, inter-sentential relation extraction task. We focus on biological contex...